Overview

Electrical power grids represent a critical infrastructure for a nation as well as strategically important. Literature review identified that power grids share basic characteristics with Supply Chain Management. This thesis presents a linear programming model to assess power grid resilience as a particular case of Supply Chain Management. Since resilient behavior is not an individual or specific system's attribute but a holistic phenomenon based on the synergic interaction within complex systems, resilience drivers in power grids were identified. Resilience is a function of Reliability, Recovery Capability, Vulnerability and Pipeline Capacity. In order to embed heterogeneous variables into the model, parameterization of resilience drivers were developed. A principle of improving resilience through redundancy was applied in the model by using a virtual redundancy in each link which allows reliability improvement throughout the entire network. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

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